QIN Xia, LI De-zhao, DENG Hua. Industrial robot trajectory tracking control based on fuzzy PD type input iterative learning[J]. 2019, (4): 66-68+72. DOI: 10.13873/J.1000-9787(2019)04-0066-03.
Aiming at the problem that the built-in controller of industrial robot in engineering application can not be modified after its structure and control parameters are determined
a fuzzy PD-type input iterative learning trajectory tracking control method based on built-in controller of robot is proposed. The method uses tracking error and its derivatives to construct the control law
and the control parameters are self-adjusted by fuzzy gain adjustment without need repeatedly adjust according to different trajectories. The iterative learning quantity is added to the trajectory input
and the actual trajectory input is updated so as to improve the tracking precision of target trajectory. The results of MATLAB/SIMULINK simulation and six degrees of freedom industrial robots experiment show that this method can achieve more accurate trajectory tracking without affecting the stability of the built-in controller of robot.